Flexible and robust control of heavy duty diesel engine airpath using data driven disturbance observers and GPR models

Diesel engine airpath control is crucial for modern engine development due to increasingly stringent emission regulations. This thesis aims to develop and validate a exible and robust control approach to this problem for speci cally heavy-duty engines. It focuses on estimation and control algorithms that are implementable to the current and next generation commercial electronic control units (ECU). To this end, targeting the control units in service, a data driven disturbance observer (DOB) is developed and applied for mass air ow (MAF) and manifold absolute pressure (MAP) tracking control via exhaust gas recirculation (EGR) valve and variable geometry turbine (VGT) vane. Its performance bene ts are demonstrated on the physical engine model for concept evaluation. The proposed DOB integrated with a discrete-time sliding mode controller is applied to the serial level engine control unit. Real engine performance is validated with the legal emission test cycle (WHTC - World Harmonized Transient Cycle) for heavy-duty engines and comparison with a commercially available controller is performed, and far better tracking results are obtained. Further studies are conducted in order to utilize capabilities of the next generation control units. Gaussian process regression (GPR) models are popular in automotive industry especially for emissions modeling but have not found widespread applications in airpath control yet. This thesis presents a GPR modeling of diesel engine airpath components as well as controller designs and their applications based on the developed models. Proposed GPR based feedforward and feedback controllers are validated with available physical engine models and the results have been very promisin

Data driven disturbance observer design and control for diesel engine airpath

Diesel engine airpath is a popular nonlinear control plant in the literature. Airpath is one of the key elements for engine out emissions control of the diesel engines. Its robust control requires controller design based on a nonlinear model of a system. Analytical model based control approaches are common in the literature. This study presents discrete sliding mode control and data driven disturbance observer design for diesel engine airpath. Identification tests and controller performance are simulated in a modeling environment where disturbance rejection capability of the developed control system is also characterized

Characterisation, control, and energy management of electrified turbocharged diesel engines

The electrification of engine components offers significant opportunities for fuel efficiency improvements. The electrified turbocharger is one of the most attractive options since it recovers part of the engine exhaust gas mechanical energy to assist boosting. Therefore, the engine can be downsized through improved transient responsiveness. In the electrified turbocharger, an electric machine is mounted on the turbine shaft and changes the air system dynamics, so characterisation of the new layout is essential. A systematic control solution is required to manage energy flows in the hybrid system. In this paper, a framework for characterisation, control, and energy management for an electrified turbocharged diesel engine is proposed. The impacts of the electric machine on fuel economy and air system variables are analysed. Based on the characterisation, a two-level control structure is proposed. A real-time energy management strategy is employed as the supervisory level controller to generate the optimal values of critical variables, while a model-based multi-variable controller is designed as the low level controller to track the values. The two controllers work together in a cascade to address both fuel economy optimisation and battery state-of-charge maintenance. The proposed control strategy is validated on a high fidelity physical engine model. The tracking performance shows the proposed framework is a promising solution in regulating the behavior of electrified engines

Modelling the exhaust gas recirculation mass flow rate in modern diesel engines

The intrinsic model accuracy limit of a commonly used Exhaust Gas Recirculation (EGR) mass flow rate model in diesel engine air path control is discussed in this paper. This EGR mass flow rate model is based on the flow of a compressible ideal gas with unchanged specific heat ratio through a restriction cross-area within a duct. A practical identification procedure of the model parameters is proposed based on the analysis of the engine data and model structure. This procedure has several advantages which include simplicity, low computation burden and low engine test cost. It is shown that model tuning requires only an EGR valve sweep test at a few engine steady state operating points. It is also shown that good model accuracy can be achieved when the control variables of other air path devices, e.g. The vane position of a Variable Geometry Turbocharger (VGT) and the torque demand of an Electric Turbo Assist (ETA), are kept constant during the EGR valve sweep test used to tune the model. Two different diesel engines are used in this work to demonstrate the model tuning procedure and the model validation results. Both engines are equipped with a high pressure external EGR system and a VGT. One of the engines has a relatively new air system device - an ETA. The model validation results of both engines show good model accuracy not only at steady state engine operating points but also during engine transients

Adaptive calibration for reduced fuel consumption and emissions

This paper presents a model-based approach for continuously adapting an engine calibration to the traffic and changing pollutant emission limits. The proposed strategy does not need additional experimental tests beyond those required by the traditional calibration approach. The method utilises information currently available in the engine control unit to adapt the engine control to the particular driving patterns of a given driver. Additional information about the emissions limits should be provided by an external structure if an adaptation to the pollutant immission is required. The proposed strategy has been implemented in a light-duty diesel engine, and showed a good potential to keep NOx emissions around a defined limit.Guardiola, C.; Pla Moreno, B.; Bares-Moreno, P.; Waschl, H. (2016). Adaptive calibration for reduced fuel consumption and emissions. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 230(14):2002-2014. doi:10.1177/0954407016636977S200220142301

ECU-oriented models for NOx prediction. Part 1: a mean value engine model for NOx prediction

The implantation of nitrogen oxide sensors in diesel engines was proposed in order to track the emissions at the engine exhaust, with applications to the control and diagnosis of the after-treatment devices. However, the use of models is still necessary since the output from these sensors is delayed and filtered. The present paper deals with the problem of nitrogen oxide estimation in turbocharged diesel engines combining the information provided by both models and sensors. In Part 1 of this paper, a control-oriented nitrogen oxide model is designed. The model is based on the mapping of the nitrogen oxide output and a set of corrections which account for the variations in the intake and ambient conditions, and it is designed for implementation in commercial electronic control units. The model is sensitive to variations in the engine's air path, which is solved through the engine volumetric efficiency and the first-principle equations but disregards the effect of variation in the injection settings. In order to consider the effect of the thermal transients on the in-cylinder temperature, the model introduces a dynamic factor. The model behaves well in both steady-state operation and transient operation, achieving a mean average error of 7% in the steady state and lower than 10% in an exigent sportive driving mountain profile cycle. The relatively low calibration effort and the model accuracy show the feasibility of the model for exhaust gas recirculation control as well as onboard diagnosis of the nitrogen oxide emissions.Guardiola, C.; Pla Moreno, B.; Blanco-Rodriguez, D.; Calendini, PO. (2015). ECU-oriented models for NOx prediction. Part 1: a mean value engine model for NOx prediction. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 229(8):992-1015. doi:10.1177/0954407014550191S9921015229

A novel predictive semi-physical feed-forward turbocharging system transient control strategy based on mean-value turbocharger model

Variable geometry turbine is a technology that has been proven on diesel engines. However, despite the potential to further improve gasoline engines’ fuel economy and transient response using variable geometry turbine, controlling the variable geometry turbine during transients is challenging due to its highly non-linear behaviours especially on gasoline applications. After comparing three potential turbocharger transient control strategies, the one that predicts the turbine performances for a range of possible variable geometry turbine settings in advance was developed and validated using a high-fidelity engine model. The proposed control strategy is able to capture the complex transient behaviours and achieve the optimum variable geometry turbine trajectories. This improved the turbocharger response time by more than 14% compared with a conventional proportional–integral–derivative controller, which cannot achieve target turbocharge speed in all cases. Furthermore, the calibration effort required can be significantly reduced, offering significant benefits for powertrain developers. It is expected that the structure of this transient control strategy can also be applied to complex air-path systems. </jats:p

Observability studies of a turbocharger systems

The use of diesel engine turbochargers is increasing today, as it represents an option that o ers high e ciency and low fuel consumption. To design the control system in order to reduce the level of exhaust emissions there is a need for information about all states that are not measurable. To this end, observers or virtual sensors are more frequently applied, achieving estimates of the system states from inputs and measured output. To propose an observer, the precise mathematical model of the air path diesel engine system is used. This is a nonlinear model of a third order which is analyzed in terms of observability. From the point of view of systems theory, certain conditions and the existence of a transformation of the system state, called di eomorphism, need to be evaluated. Observers have been designed based on di erent approaches: Extended Luenberger Observers, High Gain Observers, Sliding Modes Observers and Extended Kalman-Bucy Filters. They have been validated by simulation for the system under consideration in this work.Tesi